Analysis of the clinical findings used to diagnose coliform mastitis in dairy cows, and comparison to a prediction model.

Logistic regression was used to analyze the clinical findings (attributes) which predicted coliform mastitis in 113 dairy cattle, 36 of which had coliforms cultured from milk. Weakness of the cow, swelling of the udder, decreased body temperature and watery consistency of the milk were selected for the model. An analysis was then done to find the attributes which clinicians used when predicting that a cow would have a coliform cultured. Clinicians appeared to use water consistency of the milk, shivering, firmness of the udder, pulse rate, elevated body temperature, and respiratory rate. In a final analysis the clinicians' predictions were forced into the model to determine which attributes might be used by clinicians to increase diagnostic accuracy. Inclusion of weakness of the cow, swelling of the udder, decreased temperature of the cow, and duration of mastitis of less than 24 hours increased accuracy over clinical prediction alone. Accuracy of cowside diagnosis might be increased if more attention were paid to these attributes when making a diagnosis of coliform mastitis.

Accuracy of a discriminant analysis model for prediction of coliform mastitis in dairy cows and a comparison with clinical prediction.

We tested an equation, which had been developed previously using discriminant analysis, for predicting whether a cow has coliform mastitis. Variables indicating a high probability of coliform infection included history of previous mastitis in the affected quarter, weakness, clear or white color of milk, water consistency of the milk, swelling of the udder, lack of previous mastitis in other quarters, lack of palpable udder abscesses, and a high body temperature. Application of this predictive equation to 114 cows with mastitis to determine if they would have coliform organisms cultured from the affected quarters resulted in an accuracy of 71% (sensitivity = 0.42, specificity = 0.85), compared to an accuracy of 62% (sensitivity = .64, specificity = .61) for cowside prediction by the attending clinicians. Changing the cutoff score of the discriminant rule so that the sensitivity of the discriminant prediction was similar to that of the clinicians yielded an accuracy of 64% (sensitivity = .64, specificity = .64).

Accuracy of clinicians in predicting the bacterial cause of clinical bovine mastitis.

We examined the ability of clinicians to predict the causative organism of bovine mastitis in our practice. We obtained 118 milk culture results from 112 mastitic cows and compared the culture results to the predictions of clinicians at the time of milk sample collection. Sixty of 118 culture results were accurately predicted. The positive predictive value for coliform mastitis was 42% and the negative predictive value was 79% in a study population with a 31% prevalence of coliform mastitis. The proportion of coliform positive cultures accurately predicted was significantly greater than that expected by chance (p < 0.02).

Isolation of mastitis pathogens from quarters of cows recently treated with antimicrobial agents.

Milk samples for aerobic culturing were collected from 72 quarters of cows with clinical mastitis that had been nonresponsive to antimicrobial intramammary treatment. All samples were collected within 24 hours of the most recent treatment. Mastitis pathogens were isolated from 56 samples (78%).

Pendular nystagmus in dairy cattle.

In a survey of 2,932 mature dairy cattle performed over a 1-month period, we found 15 with rapid oscillation in 1 or both eyes. Nystagmus had been present since shortly after birth in 2 animals, and the age at onset was unknown in the others. The nystagmus was not associated with any other physical or neurologic problem. Pendular nystagmus apparently is benign and should not be mistaken for a sign of serious neurologic disease.